Just a few days ago Google launched a Generative AI learning path with courses that cover topics akin to Introduction to Generative AI, Large Language Models, Image Generation, etc.
The perfect thing is that among the courses don’t have any prerequisites and are free, so even those with no programming knowledge can profit from the courses.
Here’s all the things that you must find out about these AI courses.
Who is that this course for?
Anyone who’s curious about learning about Generative AI products, Large Language Models, and the best way to deploy Generative AI solutions should enroll on this course.
That said, among the many 10 courses offered by Google there are around 5 courses that require some knowledge in Python and Machine Learning. But, don’t worry, in the following section, I’ll talk more about each course and mention which courses don’t have any prerequisites.
By the best way, after completing a course, you’ll earn a pleasant badge just like the one below.
What does Google’s Generative AI learning path cover?
The Generative AI learning path created by Google guides you thru a curated collection of content on generative AI products and technologies.
Here’s a review of the ten courses included in the educational path.
The 5 courses below don’t have any prerequisites.
- : Explains what Generative AI is, the way it’s used, and the way it differs from traditional machine learning methods.
- Explains what LLMs are, use cases, and prompt engineering on LLMs.
- : Explains what responsible AI is, why it’s necessary, and the way Google implements responsible AI in its products.
- : Teaches you what Generative AI Studio is, its features and options, and the best way to use it.
Then again, the remainder of the courses require knowledge of Python programming, Machine learning, and Deep learning.
- Introduces you to the idea behind diffusion models, and the best way to train and deploy them on Vertex AI.
- Explains the primary components of the encoder-decoder architecture and the best way to train and serve these models.
- : Teaches how attention works and the way it might probably improve the performance of various machine learning tasks akin to translations, summarization, and query answering.
- Explains the primary components of the transformer architecture and the way it’s used to construct the BERT model.
- Teaches you the best way to create a picture captioning model by utilizing deep learning.
Easy methods to join the course
This learning path is hosted on the Google Cloud platform. Click here to take any of the courses within the Generative AI Learning Path.
Bear in mind that this isn’t the one free course available on the Google Cloud platform, but there are other cool courses just like the Data Engineer Learning Path, Data Analyst Learning Path, etc. Click here to see the entire catalog within the Google Cloud Skill Boost.
Other Free AI Courses
There are various free courses about AI on the web. One among my favorite courses is the ChatGPT Prompt Engineering Course developed by OpenAI and Andrew Ng. To know more about this course, check this text I wrote.
Also, below are 4 free prompt engineering courses that may be followed even by those with zero coding experience.
That’s it! Hope these courses enable you increase your knowledge about artificial intelligence!
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